Pattern detection module, video encoding system and method for use therewith

ABSTRACT

A system for encoding a video stream into a processed video signal that includes at least one image, includes a pattern detection module for detecting a pattern of interest in the at least one image and identifying a region that contains the pattern of interest when the pattern of interest is detected. An encoder section, generates the processed video signal and wherein, when the pattern of interest is detected, a higher quantization is assigned to the region than to portions of the at least one image outside the region.

CROSS REFERENCE TO RELATED PATENTS

The present application is related to the following U.S. patentapplication that is contemporaneously filed and commonly assigned:

PEAK SIGNAL TO NOISE RATIO WEIGHTING MODULE, VIDEO ENCODING SYSTEM ANDMETHOD FOR USE THEREWITH, having Ser. No. ______;

the contents of which is expressly incorporated herein in their entiretyby reference thereto.

TECHNICAL FIELD OF THE INVENTION

The present invention relates to encoding used in devices such as videoencoders/codecs.

DESCRIPTION OF RELATED ART

Video encoding has become an important issue for modern video processingdevices. Robust encoding algorithms allow video signals to betransmitted with reduced bandwidth and stored in less memory. However,the accuracy of these encoding methods face the scrutiny of users thatare becoming accustomed to higher resolution and better picture quality.Standards have been promulgated for many encoding methods including theH.264 standard that is also referred to as MPEG-4, part 10 or AdvancedVideo Coding, (AVC). While this standard sets forth many powerfultechniques, further improvements are possible to improve the performanceand speed of implementation of such methods.

Further limitations and disadvantages of conventional and traditionalapproaches will become apparent to one of ordinary skill in the artthrough comparison of such systems with the present invention.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 presents a block diagram representation of a video processingdevice 125 in accordance with an embodiment of the present invention.

FIG. 2 presents a block diagram representation of a PSNR weightingmodule 150 in accordance with an embodiment of the present invention.

FIG. 3 presents a block diagram representation of a video processingdevice 125 in accordance with an embodiment of the present invention.

FIG. 4 presents a block diagram representation of a pattern detectionmodule 175 in accordance with a further embodiment of the presentinvention.

FIG. 5 presents a block diagram representation of a region detectionmodule 320 in accordance with a further embodiment of the presentinvention.

FIG. 6 presents a block diagram representation of a video encodingsystem 102 in accordance with an embodiment of the present invention.

FIG. 7 presents a block diagram representation of a video distributionsystem 175 in accordance with an embodiment of the present invention.

FIG. 8 presents a block diagram representation of a video storage system179 in accordance with an embodiment of the present invention.

FIG. 9 presents a flowchart representation of a method in accordancewith an embodiment of the present invention.

FIG. 10 presents a flowchart representation of a method in accordancewith an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION INCLUDING THE PRESENTLY PREFERREDEMBODIMENTS

FIG. 1 presents a block diagram representation of a video processingdevice 125 in accordance with an embodiment of the present invention. Inparticular, video processing device 125 includes a receiving module 100,such as a set-top box, television receiver, personal computer, cabletelevision receiver, satellite broadcast receiver, broadband modem, 3Gtransceiver or other information receiver or transceiver that is capableof receiving video signals 110 from one or more sources such as abroadcast cable system, a broadcast satellite system, the Internet, adigital video disc player, a digital video recorder, or other videosource. Video encoding system 102 is coupled to the receiving module 100to encode, transrate and/or transcode one or more of the video signals110 to form processed video signal 112.

In an embodiment of the present invention, the video signals 110 caninclude a broadcast video signal, such as a television signal, highdefinition televisions signal, enhanced high definition televisionsignal or other broadcast video signal that has been transmitted over awireless medium, either directly or through one or more satellites orother relay stations or through a cable network, optical network orother transmission network. In addition, the video signals 110 can begenerated from a stored video file, played back from a recording mediumsuch as a magnetic tape, magnetic disk or optical disk, and can includea streaming video signal that is transmitted over a public or privatenetwork such as a local area network, wide area network, metropolitanarea network or the Internet.

Video signal 110 can include an analog video signal that is formatted inany of a number of video formats including National Television SystemsCommittee (NTSC), Phase Alternating Line (PAL) or Sequentiel CouleurAvec Memoire (SECAM). Processed video signal includes 112 a digitalvideo codec standard such as H.264, MPEG-4 Part 10 Advanced Video Coding(AVC) or other digital format such as a Moving Picture Experts Group(MPEG) format (such as MPEG1, MPEG2 or MPEG4), Quicktime format, RealMedia format, Windows Media Video (WMV) or Audio Video Interleave (AVI),or another digital video format, either standard or proprietary.

The video encoding system 102 includes a PSNR weighting module 150 thatwill be described in greater detail in conjunction with many optionalfunctions and features described in conjunction with FIG. 2 thatfollows.

FIG. 2 presents a block diagram representation of a PSNR weightingmodule 150 in accordance with an embodiment of the present invention. Insome circumstances, particularly when video encoding system 102 performsH264 or other encoding that includes in-loop de-blocking filtering,non-natural edges in an image (especially weak strait edges) can beblurred. PSNR weighting module 150 identifies edges in an image andweights the peak signal to noise ratio treatment of pixels identified asbeing associated with the identified edges. In particular, PSNRweighting module 150 includes an edge detection module 302 thatgenerates an edge detection signal 304 from an image 310 (either frameor field) of a video signal. A peak signal to noise ratio module 306,generates a weighted peak signal to noise ratio signal 308 based on theimage 310, an encoded image 300 that is encoded (including possiblytranscoding and transrating) from image 310, and the edge detectionsignal 304.

In an embodiment of the present invention, the edge detection signal 304identifies a plurality of edge pixels of the image 310 along or near oneor more edges that are identified in the image 310. Edge detectionmodule can use an edge detection algorithm such as Canny edge detection,however, other edge detection algorithms such as Roberts Cross, Prewitt,Sobel, Marr-Hildreth, zero-crossings, etc. can likewise be employed.Representing an M×N encoded image as f(i,j), the edge detection signal304 can be represented by W(i,j), that for each pixel of frame f(i,j),has a different value for edge and non-edge pixels in the image, such as

W(i,j)=1, for edge pixels

W(i,j)=0, for non-edge pixels

Considering the encoded image 310 to be represented by *f(i,j), and theweighted peak signal to noise ratio signal 308 to be represented byPSNR_(w), peak signal to noise ratio module 306 can operate to find,

     PSNR_(w) = 10 log₁₀(MAX_(I)²/MSE_(w))$\mspace{20mu} {{where},{{MSE}_{w} = {\sum\limits_{i = 0}^{M - 1}\; {\sum\limits_{j = 0}^{N - 1}{\left\lbrack {\left( {{f\left( {i,j} \right)},{- {{\,^{*}f}\left( {i,j} \right)}}} \right)^{2}\left( {1 + {\lambda \; {W\left( {i,j} \right)}}} \right)} \right\rbrack/\left\lbrack {\sum\limits_{i = 0}^{M - 1}\; {\sum\limits_{j = 0}^{N - 1}\; \left( {1 + {\lambda \; {W\left( {i,j} \right)}}} \right)}} \right\rbrack}}}}}$

Where λ is a weighting constant, B is the number of bits per sample inthe image and where MAX_(I) is the 2^(B)−1. As shown in the equationabove, the peak signal to noise ratio module 306 weights a signal tonoise ratio corresponding to the plurality of edge pixels differentlyfrom a signal to noise ratio corresponding to the plurality of non-edgepixels.

FIG. 3 presents a block diagram representation of a video processingdevice 125′ in accordance with an embodiment of the present invention.In particular, video processing device operates as video processingdevice 125 and video encoding system 102′ operates similarly to videoencoding system 102 but possibly without the inclusion of PSNR weightingmodule 150, but including pattern detection module 175. In particular,pattern detection module 175 can operate via clustering, statisticalpattern recognition, syntactic pattern recognition or via other patterndetection methodologies to detect a pattern of interest in an image(frame or field) of video signal 110 and identifying a region thatcontains this pattern of interest when the pattern of interest isdetected. An encoder section of video encoding system 102′ generates theprocessed video signal by quantizing and digitizing with a particularimage quality, wherein, when the pattern of interest is detected, ahigher quality, such as a lower quantization, higher resolution, orother higher quality is assigned to the region than to portions of theat least one image outside the region to provide a higher quality imagewhen encoding the region as opposed to portions of the image that areoutside of the region. For instance, the encoder section uses a greaterresolution, quantization, etc. when encoding macroblocks within theregion that it would ordinarily use if the pattern had not been detectedand the region identified. The operation of pattern detection module 175will be described in greater detail with many optional functions andfeatures in conjunction with FIGS. 4 and 5 that follow.

FIG. 4 presents a block diagram representation of a pattern detectionmodule 175 in accordance with a further embodiment of the presentinvention. In particular, pattern detection module 175 includes a regiondetection module 320 for detecting a detected region 322 in the at leastone image and wherein the region is based on the detected region. Inoperation, the region detection module can detect the presence of aparticular pattern or other region of interest that may require greaterimage quality. An example of such a pattern is a human face or otherface, however, other patterns including symbols, text, important imagesand as well as application specific patterns and other patterns canlikewise be implemented. Pattern detection module 175 optionallyincludes a region cleaning module 324 that generates a clean region 326based on the detected region 322, such via a morphological operation.Pattern detection module 175 can further include a region growing modulethat expands the clean region 326 to generate a region identificationsignal 330 that identifies the region containing the pattern ofinterest.

Considering, for example, the case where the image 310 includes a humanface and the pattern detection module 175 generates a regioncorresponding the human face, region detection module 320 can generatedetected region 322 based on the detection of pixel color valuescorresponding to facial features such as skin tones. Region cleaningmodule can generate a more contiguous region that contains these facialfeatures and region growing module can grow this region to include thesurrounding hair and other image portions to ensure that the entire faceis included in the region identified by region identification signal330. The encoding section can operate using region identification signal330 to emphasize the quality in this facial region while potentiallydeemphasizing other regions of the image. It should be noted that theoverall image may be of higher quality to a viewer given the greatersensitivity and discernment of faces.

FIG. 5 presents a block diagram representation of a region detectionmodule 320 in accordance with a further embodiment of the presentinvention. In this embodiment, region detection module 320 operates viadetection of colors in image 310. Color bias correction module 340generates a color bias corrected image 342 from image 310. Color spacetransformation module 344 generates a color transformed image 346 fromthe color bias corrected image 342. Color detection module generates thedetected region 322 from the colors of the color transformed image 346.

For instance, following with the example discussed in conjunction withFIG. 4 where human faces are detected, color detection module 348 canoperate to detect colors in the color transformed image 346 thatcorrespond to skin tones using an elliptic skin model in the transformedspace such as a C_(b)C_(r) subspace of a transformed YC_(b)C_(r) space.In particular, a parametric ellipse corresponding to contours ofconstant Mahalanobis distance can be constructed under the assumption ofGaussian skin tone distribution to identify a detected region 322 basedon a two-dimension projection in the C_(b)C_(r) subspace. As exemplars,the 853,571 pixels corresponding to skin patches from theHeinrich-Hertz-Institute image database can be used for this purpose,however, other exemplars can likewise be used in broader scope of thepresent invention.

FIG. 6 presents a block diagram representation of a video encodingsystem 102 in accordance with an embodiment of the present invention. Inparticular, video encoding system 102 operates in accordance with manyof the functions and features of the H.264 standard, the MPEG-4standard, VC-1 (SMPTE standard 421M) or other standard, to encode,transrate or transcode video input signals 110 that are received via asignal interface 198.

The video encoding system 102 includes an encoder section 103 havingsignal interface 198, processing module 230, motion compensation module240, memory module 232, and coding module 236. The processing module 230that can be implemented using a single processing device or a pluralityof processing devices. Such a processing device may be a microprocessor,co-processors, a micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on operational instructions that arestored in a memory, such as memory module 202. Memory module 232 may bea single memory device or a plurality of memory devices. Such a memorydevice can include a hard disk drive or other disk drive, read-onlymemory, random access memory, volatile memory, non-volatile memory,static memory, dynamic memory, flash memory, cache memory, and/or anydevice that stores digital information. Note that when the processingmodule implements one or more of its functions via a state machine,analog circuitry, digital circuitry, and/or logic circuitry, the memorystoring the corresponding operational instructions may be embeddedwithin, or external to, the circuitry comprising the state machine,analog circuitry, digital circuitry, and/or logic circuitry.

Processing module 230, and memory module 232 are coupled, via bus 250,to the signal interface 198 and a plurality of other modules, such asPSNR weighting module 150, pattern detection module 175, motioncompensation module 240 and coding module 236. The modules of videoencoder 102 can be implemented in software, firmware or hardware,depending on the particular implementation of processing module 230. Itshould also be noted that the software implementations of the presentinvention can be stored on a tangible storage medium such as a magneticor optical disk, read-only memory or random access memory and also beproduced as an article of manufacture. While a particular busarchitecture is shown, alternative architectures using directconnectivity between one or more modules and/or additional busses canlikewise be implemented in accordance with the present invention.

In operation, motion compensation module 240 and coding module 236operate to produce a compressed video stream based on either a videostream from one or more video signals 110. Motion compensation module240 operates in a plurality of macroblocks of each frame or field of thevideo stream generating residual luma and/or chroma pixel valuescorresponding to the final motion vector for each macroblock. Codingmodule 236 generates processed video signal 112 by transforming codingand quantizing the residual pixel values into quantized transformedcoefficients that can be further coded, such as by entropy coding inentropy coding, filtered by a de-blocking filter and transmitted and/orstored as the processed video signal 112. In a transcoding applicationwhere digital video streams are received by the encoder 102, theincoming video signals can be combined prior to further encoding,transrating or transcoding. Alternatively, two or more encoded,transrated or transcoded video streams can be combined using the presentinvention as described herein.

FIG. 7 presents a block diagram representation of a video distributionsystem 175 in accordance with an embodiment of the present invention. Inparticular, processed video signal 112 is transmitted via a transmissionpath 122 to a video decoder 104. Video decoder 104, in turn can operateto decode the processed video signal for display on a display devicesuch as television 10, computer 20 or other display device.

The transmission path 122 can include a wireless path that operates inaccordance with a wireless local area network protocol such as an 802.11protocol, a WIMAX protocol, a Bluetooth protocol, etc. Further, thetransmission path can include a wired path that operates in accordancewith a wired protocol such as a Universal Serial Bus protocol, anEthernet protocol or other high speed protocol.

FIG. 8 presents a block diagram representation of a video storage system179 in accordance with an embodiment of the present invention. Inparticular, device 11 is a set top box with built-in digital videorecorder functionality, a stand alone digital video recorder, a DVDrecorder/player or other device that stores the processed video signal112 for display on video display device such as television 12. Whilevideo encoder 102 is shown as a separate device, it can further beincorporated into device 11. While these particular devices areillustrated, video storage system 179 can include a hard drive, flashmemory device, computer, DVD burner, or any other device that is capableof generating, storing, decoding and/or displaying the combined videostream 220 in accordance with the methods and systems described inconjunction with the features and functions of the present invention asdescribed herein.

FIG. 9 presents a flowchart representation of a method in accordancewith an embodiment of the present invention. In particular a method ispresented for use in conjunction with one or more functions and featuresdescribed in conjunction with FIGS. 1-8. In step 500, the methoddetermines if a pattern of interest is detected in the image. When thepattern of interest is detected, a region is identified that containsthe pattern of interest as shown in step 502 and a higher quality isassigned to the region than to portions of the at least one imageoutside the region as shown in step 504.

In an embodiment of the present invention, the step of detecting apattern of interest in the image detects a face in the image. Step 502can generate a clean region based on a detected region and wherein theregion is based on the clean region. Step 502 can generate a cleanregion based on a morphological operation. Step 502 can further expandthe clean region to generate a region identification signal thatidentifies the region, generate a color bias corrected image from the atleast one image, generate a color transformed image from the color biascorrected image, identify the region based on colors of the at least oneimage, and/or detect facial colors in the at least one image. Step 504can be performed as part of a transcoding and/or transrating the atleast one image.

FIG. 10 presents a flowchart representation of a method in accordancewith an embodiment of the present invention In particular a method ispresented for use in conjunction with one or more functions and featuresdescribed in conjunction with FIGS. 1-9. In step 400, a encoded image isgenerated from the at least one image. In step 402, an edge detectionsignal is generated from the at least one image. In step 404, a weightedpeak signal to noise ratio signal is generated based on the at least oneimage, the encoded image and the edge detection signal.

In an embodiment of the present invention, step 402 includes Canny edgedetection. The at least one image includes a plurality of pixels thatinclude a plurality of edge pixels along at least one edge contained inthe at least one image and the edge detection signal identifies theplurality of edge pixels along the at least one edge. The edge detectionsignal can identify a plurality of non-edge pixels in the at least oneimage.

Step 404 can include weighting a signal to noise ratio corresponding tothe plurality of edge pixels differently from a signal to noise ratiocorresponding to the plurality of non-edge pixels. The encoded image canbe generated from a transcoding and/or transrating of the at least oneimage.

In preferred embodiments, the various circuit components are implementedusing 0.35 micron or smaller CMOS technology. Provided however thatother circuit technologies, both integrated or non-integrated, may beused within the broad scope of the present invention.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are possible that are notlimited by the particular examples disclosed herein are expresslyincorporated in within the scope of the present invention.

As one of ordinary skill in the art will appreciate, the term“substantially” or “approximately”, as may be used herein, provides anindustry-accepted tolerance to its corresponding term and/or relativitybetween items. Such an industry-accepted tolerance ranges from less thanone percent to twenty percent and corresponds to, but is not limited to,component values, integrated circuit process variations, temperaturevariations, rise and fall times, and/or thermal noise. Such relativitybetween items ranges from a difference of a few percent to magnitudedifferences. As one of ordinary skill in the art will furtherappreciate, the term “coupled”, as may be used herein, includes directcoupling and indirect coupling via another component, element, circuit,or module where, for indirect coupling, the intervening component,element, circuit, or module does not modify the information of a signalbut may adjust its current level, voltage level, and/or power level. Asone of ordinary skill in the art will also appreciate, inferred coupling(i.e., where one element is coupled to another element by inference)includes direct and indirect coupling between two elements in the samemanner as “coupled”. As one of ordinary skill in the art will furtherappreciate, the term “compares favorably”, as may be used herein,indicates that a comparison between two or more elements, items,signals, etc., provides a desired relationship. For example, when thedesired relationship is that signal 1 has a greater magnitude thansignal 2, a favorable comparison may be achieved when the magnitude ofsignal 1 is greater than that of signal 2 or when the magnitude ofsignal 2 is less than that of signal 1.

As the term module is used in the description of the various embodimentsof the present invention, a module includes a functional block that isimplemented in hardware, software, and/or firmware that performs one ormore functions such as the processing of an input signal to produce anoutput signal. As used herein, a module may contain submodules thatthemselves are modules.

Thus, there has been described herein an apparatus and method, as wellas several embodiments including a preferred embodiment, forimplementing a video encoding system and a pattern detection module anda peak signal to noise ratio weighting module for use therewith. Variousembodiments of the present invention herein-described have features thatdistinguish the present invention from the prior art.

It will be apparent to those skilled in the art that the disclosedinvention may be modified in numerous ways and may assume manyembodiments other than the preferred forms specifically set out anddescribed above. Accordingly, it is intended by the appended claims tocover all modifications of the invention which fall within the truespirit and scope of the invention.

1. A system for encoding a video stream into a processed video signal,the video stream including at least one image, the system comprising: apattern detection module for detecting a pattern of interest in the atleast one image and identifying a region that contains the pattern ofinterest when the pattern of interest is detected; and an encodersection, coupled to the region detection module, that generates theprocessed video signal, wherein, when the pattern of interest isdetected, a higher quality is assigned to the region than to portions ofthe at least one image outside the region.
 2. The system of claim 1wherein the pattern detection module includes a region detection modulefor detecting a detected region in the at least one image and whereinthe region is based on the detected region.
 3. The system of claim 1wherein the region detection module detects a face in the at least oneimage.
 4. The system of claim 2 wherein the pattern detection modulefurther includes a region cleaning module that generates a clean regionbased on the detected region and wherein the region is based on theclean region.
 5. The system of claim 4 wherein the region cleaningmodule uses a morphological operation.
 6. The system of claim 4 whereinthe pattern detection module further includes a region growing modulethat expands the clean region to generate a region identification signalthat identifies the region.
 7. The system of claim 2 wherein the regiondetection module includes a color bias correction module that generatesa color bias corrected image from the at least one image.
 8. The systemof claim 7 wherein the region detection module further includes a colorspace transformation module that generates a color transformed imagefrom the color bias corrected image.
 9. The system of claim 2 whereinthe region detection module includes a color detection module thatgenerates the detected region based on colors of the at least one image.10. The system of claim 9 wherein the color detection module detectsfacial colors in the at least one image.
 11. The system of claim 1wherein the encoder section transcodes the at least one image.
 12. Thesystem of claim 1 wherein the encoder section transrates the at leastone image.
 13. A method for encoding a video stream into a processedvideo signal, the video stream including at least one image, the methodcomprising: detecting a pattern of interest in the at least one image;and when the pattern of interest is detected: identifying a region thatcontains the pattern of interest; and assigning a higher quality to theregion than to portions of the at least one image outside the region.14. The method of claim 13 wherein the step of detecting a pattern ofinterest in the at least one image detects a face in the at least oneimage.
 15. The method of claim 13 wherein the step of identifying aregion generates a clean region based on a detected region and whereinthe region is based on the clean region.
 16. The method of claim 13wherein step of identifying a region generates a clean region based on amorphological operation.
 17. The method of claim 16 wherein the step ofidentifying a region further includes a expanding the clean region togenerate a region identification signal that identifies the region. 18.The method of claim 13 wherein the step of identifying a region includesgenerating a color bias corrected image from the at least one image. 19.The method of claim 18 wherein the step of identifying a region includesgenerating a color transformed image from the color bias correctedimage.
 20. The method of claim 13 wherein the step of identifying aregion can identify the region based on colors of the at least oneimage.
 21. The method of claim 13 wherein the step of identifying aregion includes detecting facial colors in the at least one image. 22.The method of claim 1 wherein the encoding includes transcoding the atleast one image.
 23. The method of claim 1 wherein the encoding includestransrating the at least one image.